Kyle R. Douglas-Mankin

Soil and Water Assessment Tool (SWAT) Hydrologic/Water Quality Model: Extended Capability and Wider Adoption

This article introduces a special collection of 16 research articles on new developments and applications of the Soil and Water Assessment Tool (SWAT) to address various environmental issues at a range of geographic and temporal scales. Highlights include addition of a subdaily erosion and sediment transport algorithm, a biozone module, and a new algorithm for shallow water table depth. Model applications include climate change impact assessments, model adaptation to regional environmental conditions, watershed-scale soil erosion assessments, and linkages to other models. A summary of reported model performance indicates that 85% of daily flow calibration statistics reported in this collection were satisfactory or better, with very good performance in four of the 20 calibration results and in three of the 19 validation results. Details of reported model parameters for calibration of flow and water quality constituents are provided for other SWAT modelers. This collection builds upon a previous ASABE 2010 SWAT Special Collection, demonstrating continued developments to enhance SWATs capabilities and highlighting SWATs continued expansion in international applications, especially in Asia.

Hydrologic and Water Quality Models: Use, Calibration, and Validation

To provide a common background and platform for consensual development of calibration and validation guidelines, model developers and/or expert users of the commonly used hydrologic and water quality models globally were invited to write technical articles recommending calibration and validation procedures specific to their model. This article introduces a special collection of 22 research articles that present and discuss calibration and validation concepts in detail for 25 hydrologic and water quality models. The main objective of this introductory article is to introduce and summarize key aspects of the hydrologic and water quality models presented in this collection. The models range from field to watershed scales for simulating hydrology, sediment, nutrients, bacteria, and pesticides at temporal scales varying from hourly to annually. Individually, the articles provide model practitioners with detailed, model-specific guidance on model calibration, validation, and use. Collectively, the articles in this collection present a consistent framework of information that will facilitate development of a proposed set of ASABE model calibration and validation guidelines.

Field-Level Targeting Using SWAT: Mapping Output from HRUs to Fields and Assessing Limitations of GIS Input Data

Soil erosion from agricultural fields is a fundamental water quality and quantity concern throughout the U.S. Watershed models can help target general areas where soil conservation measures are needed, but they have been less effective at making field-level recommendations. The objectives of this study were to demonstrate a method of field-scale targeting using ArcSWAT and to assess the impact of topography, soil, land use, and land management source data on field-scale targeting results. The study was implemented in Black Kettle Creek watershed (7,818 ha) in south-central Kansas. An ArcGIS toolbar was developed to post-process SWAT hydrologic response unit (HRU) output to generate sediment yields for individual fields. The relative impact of each input data source on field-level targeting was assessed by comparing ranked lists of fields on the basis of modeled sediment-yield density (Mg ha-1) from each data-source scenario. Baseline data of field-reconnaissance land use and management were compared to NASS and NLCD data, 10 m DEM topography were compared to 30 m, and SSURGO soil data were compared to STATSGO. Misclassification of cropland as pasture by NASS and aggregation of all cropland types to a single category by NLCD led to as much as 75% and 82% disagreement, respectively, in fields identified as having the greatest sediment-yield densities. Neither NASS nor NLCD data include land management data (such as terraces, contour farming, or no-till), but such inclusion changed targeted fields by as much as 71%. Impacts of 10 m versus 30 m DEM topographic data and STATSGO versus SSURGO soil data altered the fields targeted as having the highest sediment-yield densities to a lesser extent (about 10% to 25%). SWAT results post-processed to field boundaries were demonstrated to be useful for field-scale targeting. However, use of incorrect source data directly translated into incorrect field-level sediment-yield ranking, and thus incorrect field targeting. Sensitivity was greatest for land use data source, followed closely by inclusion of land management practices, with less sensitivity to topographic and soil data sources.

Opinion: Endogenizing culture in sustainability science research and policy

Integrating the analysis of natural and social systems to achieve sustainability has been an international scientific goal for years (1, 2). However, full integration has proven challenging, especially in regard to the role of culture (3), which is often missing from the complex sustainability equation. To enact policies and practices that can achieve sustainability, researchers and policymakers must do a better job of accounting for culture, difficult though this task may be.

Fecal Bacteria Source Characterization and Sensitivity Analysis of SWAT 2005

The Soil and Water Assessment Tool (SWAT) version 2005 includes a microbial sub-model to simulate fecal bacteria transport at the watershed scale. The objectives of this study were to demonstrate methods to characterize fecal coliform bacteria (FCB) source loads and to assess the model sensitivity to five user-defined model parameters (BACTKDQ: bacteria soil partition coefficient in surface runoff, TBACT: temperature adjustment factor, WDLPQ: less-persistent bacteria die-off in solution phase, WDLPS: less-persistent bacteria die-off in sorbed phase, and BACTKKDB: bacteria partition coefficient in manure) and one input parameter (BACTLPDB: FCB concentration in manure). Fecal bacterial source loads were described and applied spatially for confined livestock, seasonal grazing livestock, failing human septic systems, and indigenous large mammal, small mammal, and avian wildlife. The relative sensitivity index (S) was tested using the independent parameter perturbation (IPP) method. Validation results for an uncalibrated SWAT model using nine runoff events from Rock Creek watershed (77 km2) were considered adequate to proceed with sensitivity analyses. Flow simulation resulted in good coefficient of determination (R2) of 0.67 and Nash-Sutcliffe Efficiency Index (E) of 0.55, and FCB source load characterization methods were sufficiently precise to result in fair correlation (R2 = 0.29) and reasonable measured vs. predicted response slope (0.69). Within the ranges recommended for use in SWAT, BACTKDQ had moderate sensitivity (S < 2.67) within -99.5% from 175 (baseline value), BACTLPDB had low sensitivity (S < 0.25) within -90% from 3.29 × 107 cfu 100 mL-1, BACTKKDB had low sensitivity (S < 0.12) within -89% from 0.9, TBACT had low sensitivity (S < 0.36) ±20% from 1.07, WDLPQ had low sensitivity (S < 0.25) ±50% from 0.23, and WDLPS had no sensitivity (S < 0.06) ±50% from 0.023 when compared with all surface runoff events. This study recommends that SWAT could adopt default values of 0.23 for WDLPQ and 0.023 for WDLPS without adversely affecting results. Moderate sensitivity for BACTKDQ indicates that users should select these with caution considering locally relevant data. The sensitivity of BACTKDQ was found high when compared with nine measured surface runoff events.

Seasonal and Annual Impacts of Climate Change on Watershed Response Using an Ensemble of Global Climate Models

Climate change impacts watershed hydrology and contributes to alteration of hydrologic regimes in streams. However, global climate models (GCMs) operate at spatial and temporal scales that are too large to capture important watershed-scale hydrologic shifts. A method of disaggregating monthly ensemble GCM data into temperature and precipitation data series for daily, watershed-specific hydrologic simulations with SWAT was developed and assessed in the Soldier Creek watershed in northeast Kansas. A stochastic weather generator (WINDS) was employed to produce a baseline scenario (no changes from late 20th century conditions) and two scenarios based on ensemble means of 15 GCMs representing future conditions (A2 storyline) referred to as the 2050 and 2100 scenarios. Future hydrologic regimes exhibited non-linear annual and monthly responses in hydrologic budget components, such as surface runoff, baseflow, and soil moisture, to temperature and precipitation changes. For the 2050 scenario, the combination of higher temperatures along with decreased annual precipitation and increased spring precipitation resulted in higher surface runoff, baseflow, and streamflow in May and June with a longer drought season later in summer. The significant decrease in streamflow, runoff, and baseflow for the 2100 scenario reflected an increase in monthly and annual temperature rather than a direct result of precipitation decline. The 2100 scenario also produced a reduction in low-flow duration, an increase in the number of drought occurrences, and a decrease in flood frequency and duration. In retrospect, use of the stochastic weather generator to temporally downscale monthly GCM results while incorporating site-specific climate variability (such as occurs with convective storms often missed in coarse-resolution GCM data) produced more meaningful analysis of hydrological impacts, which is critical to predicting and understanding the impacts of climate change. Although this method allowed simulation of future-climate shifts based on GCM-simulated monthly shifts, it could not simulate potential shifts in climate patterns within a month, such as changes in transitional probabilities that govern the intensity and distribution of storms with months. In future work, translation of regional climate model responses into WINDS stochastic parameter adjustments will allow more accurate and efficient simulation. The severity of the increased drought and decreased flood responses simulated in this study would not be anticipated by review of precipitation trends alone nor by analysis of annual hydrologic responses alone. Similarly, many critical hydrologic responses reflected interactions between climate variables (e.g., precipitation and temperature) at sub-annual temporal scales, which highlights the need to consider climatic interactions in future studies of climate change impacts.

Paying for sediment: Field-scale conservation practice targeting, funding, and assessment using the Soil and Water Assessment Tool

Watershed models have been widely used to estimate soil erosion and evaluate the effectiveness of conservation practices at different temporal and spatial scales; however, little progress has been made in applying these theoretical model results to the practical challenge of allocating conservation practice funding to meet specific soil loss objectives. Black Kettle Creek subwatershed (7,809 ha [19,295 ac]) of Little Arkansas River Watershed (360,000 ha [889,579 ac]) in south central Kansas was the focus of an innovative project to target conservation practice funding and pay directly for modeled sediment reduction. Detailed data (10 m [33 ft] digital elevation model topography, Soil Survey Geographic database soils, and a manually developed land use/land cover layer) were input into the Soil and Water Assessment Tool model, and the calibrated model was used to quantify soil erosion for each field. Effectiveness of locally relevant best management practices (BMPs) was simulated for each field. The simulated field-scale effectiveness for implemented BMPs ranged from 9% to 83% for single BMPs and 67% to 100% for selected combinations of BMPs. An in-field signup sheet was developed with field-specific sediment loss–based payments calculated for each BMP option. BMP implementation was 16.7% of cropland area prior (preinstalled BMPs) to the project, and 30.6% of cropland area (postinstalled BMPs) was added due to project-funded implementation. Postinstalled BMP implementation (47.3% of cropland) resulted in 35.8% sediment yield reduction compared to the no-BMPs scenario and 21.9% reduction compared to preinstalled BMP conditions, which was better than initially projected for this project. Inclusion of nontargeted fields and less-than-optimal BMPs had no influence on achieving soil loss objectives because payments were based on implemented soil loss rather than implemented area. Targeting of conservation practices based on payments scaled directly by project outcome (in this case, dollars per ton of sediment reduction) using a modeling approach allowed flexibility for both adopters (farmers) and funders (project staff) while assuring the project objective (i.e., sediment reduction) was met.

Pasture BMP effectiveness using an HRU-based subarea approach in SWAT

Many conservation programs have been established to motivate producers to adopt best management practices (BMP) to minimize pasture runoff and nutrient loads, but a process is needed to assess BMP effectiveness to help target implementation efforts. A study was conducted to develop and demonstrate a method to evaluate water-quality impacts and the effectiveness of two widely used BMPs on a livestock pasture: off-stream watering site and stream fencing. The Soil and Water Assessment Tool (SWAT) model was built for the Pottawatomie Creek Watershed in eastern Kansas, independently calibrated at the watershed outlet for streamflow and at a pasture site for nutrients and sediment runoff, and also employed to simulate pollutant loads in a synthetic pasture. The pasture was divided into several subareas including stream, riparian zone, and two grazing zones. Five scenarios applied to both a synthetic pasture and a whole watershed were simulated to assess various combinations of widely used pasture BMPs: (1) baseline conditions with an open stream access, (2) an off-stream watering site installed in individual subareas in the pasture, and (3) stream or riparian zone fencing with an off-stream watering site. Results indicated that pollutant loads increase with increasing stocking rates whereas off-stream watering site and/or stream fencing reduce time cattle spend in the stream and nutrient loads. These two BMPs lowered organic P and N loads by more than 59% and nitrate loads by 19%, but TSS and sediment-attached P loads remained practically unchanged. An effectiveness index (EI) quantified impacts from the various combinations of off-stream watering sites and fencing in all scenarios. Stream bank contribution to pollutant loads was not accounted in the methodology due to limitations of the SWAT model, but can be incorporated in the approach if an amount of bank soil loss is known for various stocking rates. The proposed methodology provides an adaptable framework for pasture BMP assessment and was utilized to represent a consistent, defensible process to quantify the effectiveness of BMP proposals in a BMP auction in eastern Kansas.

Impacts of Climate Change on Hydrologic Indices in a Northeast Kansas Watershed

Great Plains watersheds contribute to the diminishing North American unpolluted surface water supply as well as provide habitat for a number of threatened or endangered species. The number and size of these important systems has been greatly reduced by agriculture and urbanization. Climate change could pose an even greater threat to these endangered systems. There are many climate change scenarios that predict varying changes in future temperature and precipitation amounts for the Great Plains Region. In this study, two Global Climate Model (GCM) scenarios were analyzed to determine monthly rainfall and precipitation trends from 2000 to 2100. The trends were applied to the actual monthly precipitation and temperature distributions in a Northeast Kansas watershed. Daily weather data were simulated for 100 years using the WINDS weather generator. These simulations were input into the Soil and Water Assessment Tool (SWAT) hydrologic model. The streamflow output from these simulations was input into the Indicators of Hydrologic Alteration (IHA) software, which calculated multiple hydrologic indices that were compared back to a baseline scenario. The analysis showed that these climate change scenarios caused a varying increase in mean monthly streamflow patterns as well as a reduction in low flow occurrences and durations. Flood frequency and duration showed varying changes based on the individual scenario. This analysis shows that climate change scenarios have an effect on terrestrial and aquatic ecosystems in the Great Plains Region.

Monitoring and Estimating Ephemeral Gully Erosion using Field Measurements and GIS

Ephemeral gully (EG) erosion has been recognized as a major source of sediment in agricultural watersheds. Over the past few decades, soil erosion caused by sheet and rill erosion has been studied extensively, and field and watershed-scale models have been used to quantify contributions of sheet and rill erosion. In recent years, many studies have been conducted to understand EG formation, location and model development. The overall goal of this study was to develop a method to locate the potential EGs and further develop a simple model to estimate EG erosion at the watershed scale. To achieve this goal, several EGs were monitored, measured and overall characteristics described. Therefore, this paper focuses on monitoring and estimating sediment yields of few EGs in north eastern and south central Kansas.